1 What is known of Arctic kelps?

1.1 Known

  • Little is known of kelp in the Arctic

1.2 Past

  • Trading in Alaria along Baffin Island coast

1.3 Present

  • There should be other Laminariales sp. … but where?

1.4 Other

  • RWS: Other examples?

2 ArcticKelp project

  • There must be kelp in the Arctic
  • RWS: Bullet about what ArcticKelp seeks toa ccomplish
  • We don’t know what the drivers of their distributions are
  • The Arctic is changing quickly so we should figure this out ASAP
  • Where are kelp in the Arctic and what drives their distribution?
  • Does this differ for different functional groups?
    • Total kelp cover
    • Laminariales (Laminaria sp. + Sacharina sp.)
    • Agarum
    • Alaria

2.1 Campaigns

2.2 Sites

2.3 Mean cover

3 Environmental conditions

3.1 Abiotic data

  • NAPA (3-Oceans) model
    • Model outputs supplied by the Bedford Institute of Oceanography (BIO)

    • Based on the NEMO community ocean model

      (Madec and others, 2015)
    • Ice from the LIM3 model

      (Rousset et al., 2015; Vancoppenolle et al., 2009)
    • Daily surface resolution: 1998 to 2015
    • Five day (pentad) resolution at 75 depth layers
    • Tri-polar grid
      • 10 to 20 km resolution

3.2 Biotic data

  • Bio-ORACLE
    • 18 total geophysical, biotic and environmental variables
    • Surface and benthic coverage; min, mean, max, and range for most
    • Collection from many different datasets
    • 5 arcdegree spatial resolution (~9.2 km at the equator)

(Assis et al., 2018; Tyberghein et al., 2012)

4 Modelling distribution

  • Which variables are important?
  • What is the accuracy of the model?
  • What is the range in accuracy?
  • What is the distribution of inaccuracy?

4.1 Methods

  • Highly correlated variables were removed
  • A random forest model was used
  • After many iterations the best variables were found
  • These were used for many iterations to find the best model

4.2 Variables

4.2.1 Total kelp

Data layer Units Count
Sea water temperature (mean at min depth) °C 1000
Dissolved oxygen concentration (mean at min depth) mol/m 1000
Sea ice thickness (mean) m 1000
Ice fraction 1 1000
Ice concentration for categories % 1000
Phosphate concentration (mean at min depth) mol/m 1000
Ice divergence 1e-8s-1 998
Depth m 995
Sea ice thickness (range) m 992
wind stress module N/m2 988

4.2.2 Laminariales

Data layer Units Count
Depth m 1000
Latitude degree 1000
Longitude degree 1000
Photosynthetically available radiation (mean) Einstein/m/day 1000
brine salt flux 0.001*kg/m2/day 1000
Sea ice thickness (mean) m 1000
Sea Water Salinity 0.001 1000
Sea Surface Salinity 0.001 1000
Sea ice thickness (range) m 1000
Mixed Layer Depth (dsigma = 0.01 wrt 10m) m 999

4.2.3 Agarum

Data layer Units Count
Ice thickness (cell average) m 1000
Light at bottom (mean at min depth) mol/m/s 1000
Iron concentration (mean at min depth) mol/m 1000
Primary production (mean at min depth) g/m/day 1000
Chlorophyll concentration (mean at min depth) mg/m 1000
Carbon phytoplankton biomass (mean at min depth) mol/m 1000
Ice velocity along i-axis at I-point (ice presence average) m/s 1000
Dissolved oxygen concentration (mean at min depth) mol/m 1000
Current velocity (mean at min depth) m/s 998
Sea water salinity (mean at min depth) PSS 998

4.2.4 Alaria

Data layer Units Count
Depth m 1000
total flux at ocean surface W/m2 1000
non-solar heat flux at ocean surface W/m2 1000
Sea Surface Salinity 0.001 1000
sea surface height m 1000
non solar Downward Heat Flux W/m2 1000
Sea Water Salinity 0.001 999
Nitrate concentration (mean at min depth) mol/m 987
Sea water temperature (mean at min depth) °C 974
Sea Surface Temperature °C 957

4.3 Confidence

4.3.1 Total cover

4.3.2 Laminariales

4.3.3 Agarum

4.3.4 Alaria

5 Results

  • Note that the colour scales are not the same between figures

5.1 Total cover

5.2 Laminariales

5.3 Agarum

5.4 Alaria

6 Acknowledgements

Dr. Youyu Lu and Dr. Xianmin Hu for NAPA model access

This research was undertaken thanks in part to funding from the Canada First Research Excellence Fund, through the Ocean Frontier Institute.

References

Assis, J., Tyberghein, L., Bosch, S., Verbruggen, H., Serrão, E. A., and De Clerck, O. (2018). Bio-oracle v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography 27, 277–284.

Madec, G., and others (2015). NEMO ocean engine.

Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., et al. (2015). The louvain-la-neuve sea ice model lim3. 6: Global and regional capabilities.

Tyberghein, L., Verbruggen, H., Pauly, K., Troupin, C., Mineur, F., and De Clerck, O. (2012). Bio-oracle: A global environmental dataset for marine species distribution modelling. Global ecology and biogeography 21, 272–281.

Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and Maqueda, M. A. M. (2009). Simulating the mass balance and salinity of arctic and antarctic sea ice. 1. Model description and validation. Ocean Modelling 27, 33–53.